Artificial intelligence hydrology (31 résultats)

hardcover. Etat : Very Good.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : New.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Hardback. Etat : New.

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Etat : New.

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Paperback. Etat : new. Paperback. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology.In Focus a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Etat : New. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology. In Focus - a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.…

Etat : New. 2024. paperback. . . . . .

Etat : As New. Unread book in perfect condition.

Etat : NEW.

Paperback. Etat : New. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology. In Focus - a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.…

Paperback. Etat : Brand New. 160 pages. 9.25x6.12x0.75 inches. In Stock.

Paperback / softback. Etat : New. New copy - Usually dispatched within 3 working days.

Taschenbuch. Etat : Neu. Neuware - Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development. This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology. In Focus - a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.…

Etat : New. 2024. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Etat : New. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology. In Focus - a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.…

Hardback. Etat : New.

Paperback. Etat : new. Paperback. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology.In Focus a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Etat : New. Nowadays, hydrological systems are becoming increasingly complex owing to the growing interaction between nature and humans at the local scale of river sections, lakes, reservoirs, catchments, etc., to the global scale. There is great demand for the development of models to evaluate, predict, and optimize the performance of complex hydrological systems whose behavior is characterized by a strong nonlinearity. However, traditional approaches can hardly handle this nonlinear behavior; moreover, the analysis of hydrological systems at the large scale, even global, requires dealing with large-volume and real-time data. In recent years, artificial intelligence (AI), especially deep learning, has shown great potential to process massive data and solve large-scale nonlinear problems. AI has been successfully applied to computer vision, machine translation, bioinformatics, drug design, and climate science. AI models have produced results comparable to and even better than expert human performance. It is expected that AI can significantly contribute to hydrology research as well as development.This book presents some of the latest advances in the field of AI in hydrology. Both theoretical and experimental chapters are included, covering new and emerging AI methods and models from various challenging problems in hydrology. In Focus - a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.…

HRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.…